Orchestration of
differentiation, migration and re-assembly of cells is one of the most
fundamental aspects of pattern formation of tissues and organs, including
central nervous system. We thought that these coordinated behaviors of cells are
regulated by a genetic program, in which pivotal genes regulate these steps in a
tight and precise manner. This also implies that careful dissection of this
genetic program and detailed analyses of functions of genes should help us to
understand complicated morphogenesis of tissues and organs. Nonetheless, we have
just come to a point to re-evaluate our approaches and to proceed to a new
field, which has never been explored.

Pattern formation, such as the Benard convection and the
Taylor
instability, is also extensively studied in physics and chemistry. In these
cases, a homogenous group of molecules can form orderly patterns. In another
case, oxidative and reductive states repeat in an oscillatory way, known as the
(Belousov-Zhabotinsky) B-Z reaction. These indicate that autonomous mechanisms
do exist even in developing embryos, some of which were already studied
extensively by Turing and Meinhard.

We have been
exploring molecular mechanisms of pattern formation of vertebrate embryos, with
central nervous system, limb bud and heart as model organs, and with several key
transcription factors as our keen interest. Nonetheless, we have noticed that
extensive analyses on the genetic programs are not sufficient for understanding
thoroughly the dynamic pattern formation of developing embryos. Recently, we
have identified that several proteins change their shapes and conformation in
response to physical forces that are generated by cells, hereby such strains
trigger next biochemical responses. We are now studying this novel mechanism to
understand functional roles of physical forces generated by cells and sensed by
cells.

In
this research, we developed the program that is able to automatically carry out
quantitative and qualitative image analysis of mouse adipose tissues (WAT, BAT,
Beige/Brite) by using X-ray CT data.

You
can easily generate 2D and 3D images that have analysis accuracy of single-voxel
(WAT: 21.7 cells per single-voxel, BAT: 123 cells per single-voxel). We will
broadly provide these tools to wet-lab
researchers.

Copyright acknowledgement
Dr.
Akihiro Nakaya also has a part of the copyright of this program. Please refer to
Dr. Akihiro Nakaya (Niigata Univ.) and Keiko Ogura (IDAC., Tohoku Univ.) in any
presentation at meetings and an article with images or graphs that you made with
this program.

Copyright acknowledgement
Dr. Akihiro Nakaya also has a part
of the copyright of this program. Please refer to Dr. Akihiro Nakaya
(Niigata Univ.) and Keiko Ogura (IDAC., Tohoku Univ.) in any presentation at meetings
and an article with images or graphs that you made with this program.

You can also make the
ROI histogram from input data using ROI select tool in OsiriX
with our new tools HERE !

Copyright acknowledgement
Please refer to Keiko Ogura
(IDAC., Tohoku Univ.) and Keisuke Izumi (GSIS., Tohoku Univ.) in any presentation at
meetings and/or any article with images or graphs that you made with our program.